@article{discovery1489584,
           pages = {780--790},
            note = {Copyright {\copyright} 2016 American Association for Cancer Research. The published version of record is available at http://dx.doi.org/10.1158/1055-9965.EPI-15-1039},
          volume = {25},
         journal = {Cancer Epidemiology, Biomarkers \& Prevention},
            year = {2016},
           title = {Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity and Hormone-Related Risk Factors},
           month = {May},
          number = {5},
             url = {http://dx.doi.org/10.1158/1055-9965.EPI-15-1039},
            issn = {1538-7755},
        abstract = {BACKGROUND: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene-environment interactions related to hormone-related risk factors could differ between obese and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case-control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. RESULTS: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 {$\times$} 10(-6)) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 {$\times$} 10(-5)). The most notable obesity-gene-hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 {$\times$} 10(-6)). CONCLUSIONS: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2 Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility.},
          author = {Usset, JL and Raghavan, R and Tyrer, JP and McGuire, V and Sieh, W and Webb, P and Chang-Claude, J and Rudolph, A and Anton-Culver, H and Berchuck, A and Brinton, L and Cunningham, JM and DeFazio, A and Doherty, JA and Edwards, RP and Gayther, SA and Gentry-Maharaj, A and Goodman, MT and H{\o}gdall, E and Jensen, A and Johnatty, SE and Kiemeney, LA and Kjaer, SK and Larson, MC and Lurie, G and Massuger, L and Menon, U and Modugno, F and Moysich, KB and Ness, RB and Pike, MC and Ramus, SJ and Rossing, MA and Rothstein, J and Song, H and Thompson, PJ and van den Berg, DJ and Vierkant, RA and Wang-Gohrke, S and Wentzensen, N and Whittemore, AS and Wilkens, LR and Wu, AH and Yang, H and Pearce, CL and Schildkraut, JM and Pharoah, P and Goode, EL and Fridley, BL and Ovarian Cancer Association Consortium, . and Australian Cancer Study, .}
}